This tutorial deals with advanced, novel digital and intelligent sensor systems design and its applications in smartphones, tablets and IoT. Coming technological limitations, and challenges will be outlined, and new technological trends will be described in details. The integration of designed and developed microelectronic components (Universal Frequency-to-Digital Converters (UFDC) and Universal Sensors and Transducers Interface (USTI) Series of ICs) into sensor systems has the potential to greatly simplify the design of the system and contribute to further increasing of system level integration, flexibility and functionality.

The major benefits offered by such approach are high reliability, high metrological performance, wide functionality, cost effectiveness and scalability.

For data analysis, typically we load the data into a dedicated tool, like a relational database, the statistic program R, mathematica, or some other specialized tools to perform our analysis. But often, there is also another option, which can be performed on nearly every computer, having the necessary amount of storage available. Many shells, like bash, csh, … provide a bunch of powerful tools to manipulate and transform data and also to perform some sort of analysis like aggregation, etc. Beside the free availability, these tools have the advantage that they can be used immediately, without transforming and loading the data into the target system before, and also, that they typically are stream based and so, huge amounts of data can be processed, without running out of main-memory. With the additional use of gnuplot, ambitious graphic plots can easily be generated.

The aim of this tutorial is to present the most useful tools like cat, grep, sed, awk, comm, join, split, bzip2, bzcat, bzgrep, etc., and give an introduction on how they can be used together. So, for example, a wide number of queries which typically will be formulated with SQL, can also be performed using the tools mentioned before, as it will be shown in the tutorial.

The tutorial will also include hands-on parts, in which the participants do a number of practical data-analysis and transformation tasks.

Digital marketing is becoming particularly important for businesses, with its market size measuring hundreds of billions of dollars worldwide. Software platforms track consumers’ habits on the internet (preferences and needs) and provide big data to digital marketing agents. Despite the fact that Data analytics techniques are employed to assist in decision making, digital marketing do not exploit these data by taking advantage of IoT in order to understand the individual customer and customize the marketing strategy (place, time ...) to his/her needs.

Therefore, the need for accountability in digital marketing and the missing link between web analytics, IoT, business strategy and customisation raise several challenges that are discussed in this tutorial.

The tutorial aims to provide a framework for understanding the current state but also the anticipated transformation of digital marketing from a data driven perspective.

The broad nature of service quality and customization is discussed and contrasted with the digital marketing data availability. It discusses the importance of data analytics in formulating digital marketing strategies and comments on the transformational role of the Internet of Things that is expected to unveil the individual customer priorities and to enable servitisation. Emphasis is given on multicriteria decisions making and fuzzy cognitive maps. A specific case study is used to illustrate the framework and the concepts involved.